Predictive Analytics Techniques in Education by Artificial Intelligence Tools for Enhancing Academic Assessment: Systematic Review | ||
| المجلة الدولية للتعليم الإلکتروني | ||
| Volume 13, Issue 2, August 2024, Pages 91-115 PDF (828.23 K) | ||
| Document Type: البحوث والدراسات والمقالات المستوفاة للقواعد العلمية المتعارف عليها، والتى يجريها أو يشارک فى إجرائها أعضاء هيئة التدريس والباحثون فى الجامعات ومراکز البحوث المصرية والعربية، وذلک باللغتين العربية والإنجليزية . | ||
| DOI: 10.21608/ijel.2024.401345 | ||
| Author | ||
| PhD: Randa Moussa Borghosh | ||
| PhD researcher in educational technology, Faculty of Education, Mansoura University Teacher at the Ministry of Education, State Kuwait randa.moussa@std.mans.edu.eg | ||
| Abstract | ||
| This systematic review examines the impact of AI tools in predictive analytics to enhance academic assessment, AI-powered predictive analytics are gaining momentum rapidly in the education sector, where applications of predictive analytics in education include: predicting academic performance and identifying at-risk students, customizing learning, adapting education to the individual needs of learners, enabling early detection of learning difficulties, improving academic advising to help students make informed decisions about their educational paths, as well as enhancing The research also discusses the role of AI in enhancing academic assessment that includes automated correction and adaptive feedback, plagiarism detection, learning data analytics, and the development of new assessment methods, and discusses challenges related to the application of these tools across different educational contexts, including ethical considerations, data quality, algorithmic bias, privacy concerns, and accountability. The PRISMA 2020 model was used, where the previous literature and studies related to the research topic were reviewed from 2020 to 2024, and various databases such as Scopus, Springer, Google Scholar were used to identify the most relevant literature within this time frame, the 47 studies, then the best and most relevant studies were selected for further analysis, 7 studies, a comparative analysis of these studies was performed, followed by a final report to conclude the results and answer the research questions, the results of this research concluded the need to expand In the use of artificial intelligence tools for predictive analytics in evaluating students starting from primary to university, it was proposed to develop the educational system starting from kindergarten to twelfth grade, and to cancel the quarterly and final tests and replace them with modern evaluation methods such as electronic projects and scientific research in addition to weekly and monthly tests, and rely on predictive analysis in determining the student's field of specialization based on predictive analysis of the student's big data according to his tendencies. Keywords: Artificial Intelligence, AI Tools, Education, Educational Technology, Predictive Analytics, Academic Assessment, Systematic Review. | ||
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